Exploring the concept of data-driven marketing by looking at the history of data-driven challenges, the benefits of using this approach, and its limitations.
Data-driven marketing refers to the methodology of extracting actionable insights tied to consumer behavior from large data sets to predict consumer behavior in relation to new products, marketing positioning and users’ likelihood of interacting with a brand.
With the increase in popularity of Big Data and the technological advancements that allow for massive amounts of information to be collected, organized and analyzed, data-driven marketing is emerging as the next generation strategy to effectively create personalized and relevant consumer experiences.
Modern marketers know that going on gut instinct is not enough in the digital world.
Clients have high expectations and want to see immediate results. Data-backed metrics can help marketers maximize success and transform the way business is conducted online.
In this comprehensive guide, we will explore the concept of data-driven marketing by looking at the history of data-driven challenges, the benefits of using this approach, and its limitations. We will also cover a few tangible examples of data-driven marketing and the results they produced.
Data-Driven Marketing: The Business Case
Here are some interesting facts about data-driven marketing.
- A study by Forbes showed that 64% of executives “strongly agree” that data-driven marketing provides a competitive edge in deciding on how to compete with other companies in the same field.
- According to Media Math, 53% of digital marketers said “a demand to deliver more relevant communications/be more ‘customer-centric’” is one of the top driving factors for companies who are investing in data-driven marketing.
- Furthermore, eMarketer reports that 90.7% of US advertisers and marketers segment data to better target and engage with their customers. In fact, over half said that they were more advanced in that area than even five years ago. eMarketer also reports that 92.3% of organizations maintain databases to host information on customers or prospects, at least to some extent.
- Finally, this report shows that marketing teams who regularly use integrated marketing technologies are 57% more effective and productive at delivering positive ROI through their work.
- All these facts and figures are pointing in the same direction: data-driven marketing is the way forward and the key to satisfying and creating loyal customers now and into the future.
How Did It All Begin? The History of Data-Driven Marketing
The humble beginning of a data-driven marketing approach dates back to the invention of the first Customer Relationship Management (CRM) system. CRMs represent databases that are leveraged to gather, record, and store customer information which can be leveraged to increase sales, up-sell or cross-sell a specific product or service.
V12 data statistics show that 52% of consumers (and 65% of B2B buyers) say they’re likely to switch brands if a company doesn’t personalize communications to them. CRMs are vital to the tracking, collecting, and usage of data that can lead to personalized approaches to marketing.
For a full history of the CRM, there is an excellent article over at FinancesOnline, but for this piece, we’ll summarize it here.
The first CRM systems were first launched in the 1970s, and the mass adoption of marketing techniques like sales force automation, consumer information records and hotline numbers. Yes, it’s hard to believe, but we’ve been harassed by unwanted calls from telemarketers for almost 50 years now!
By the 1980s, database marketing started to become a thing. It was during this period that marketers realized that connecting on a personal level with their customers could lead to higher conversions. So instead of cold calling each potential consumer with the same message, marketers started to create different call scripts for different customer personas.
In the 1990s, this evolved into sales force automation that became the first real CRM framework. One database which could manage a company’s contacts, leads and potential opportunities in a single platform. By the end of the century, the first mobile CRM was launched. However, mobile use was limited due to the constraints of technology at the time.
And of course, over the last two decades, with the rapid growth of social media platforms (remember hi5 and Myspace?), marketers adopted their strategies to better engage with consumers at a personal level.
Today, CRM is integral to social marketing so that content can be sent straight to the correct targets – so much so that social analytics is becoming just as important as ‘standard’ analytics.
This slowly paved the path to personalization.
Automation and the introduction of cloud-based CRM systems accelerated the collection of relevant data, therefore paving the way to the emergence of data-driven marketing techniques. Nowadays, marketers can easily devise new strategies to connect with customers at a personal level based on behavioral patterns shown in the data collected about current and potential clients.
The Current State of Data-Driven Marketing
Today’s CRM is significantly more potent than at any point in the past (think of the first generation iPhone versus an iPhone XR!). CRMs lie at the heart of business with the aim of engaging with customers with tailored messages.
Previously, marketing messages had one message for everyone. With the collection of relevant data, this approach changed dramatically.
With this came personalization and targeted advertisement techniques – the foundational value adds behind data-driven marketing.
Nowadays, the best example of data-driven marketing is how consumers surfing the web or ‘chilling’ on social media see super-targeted ads that are relevant to them and engage with new brands as a result of these relevant ads.
Here are some effects that data-driven marketing has had on marketers all over the world:
First Names In Emails
While this seems standard now, this personalization technique was not commonly used back in the day. Marketers need to be using their recipients’ first names in either the body or the subject line at the very least. This is because it instantly connects them with the content, making them more likely to purchase a product.
Marketing automation has helped tailor the customer experience for visitors as it gives them precisely what they are looking for at the right time. For example, automation software can be used to send specific emails based on where a customer is in the purchase funnel if they haven’t replied in 2 days, sending them a follow-up. The first marketing automation emails are believed to have been sent around 2001.
Data-driven marketing also enables marketers to understand the type of content their audience is looking for, allowing for more personalized service. They can pinpoint the topics that each demographic requires and create a specific marketing campaign.
The Next Stage – Data-Driven Marketing Personalization
Personalization in data-driven marketing refers to the combination of creative (the ad) media (the channel) and data (about the customer).
Systems have become more sophisticated now with each of these three components becoming a collection of multiple sub-components, each informing ‘parallel-track’ marketing campaigns based on the specific traits of each demographic targeted by a marketing team.
What Are Data-Driven Creatives?
Data-driven creative uses insights and machine learning to create personalized ads to boost the return on investment for a specific media campaign. These ‘smart’ creatives provide actual value to the customer that leads them to take action.
At ComboApp, we use ‘smart’ creatives all the time.
The simplest example is this. Say we’re launching a new social media ad campaign against a specific demographic for a dating app.
We will launch the campaign against 30-40 different creatives where we test both images and text. Based on the engagement levels with these ads we see in our programmatic ad platforms, we remove all non-performing ads and focus on the ones that perform the best. Platforms like Facebook, Linkedin, or Twitter all make it very easy for agencies to test, in real-time, the effectiveness of their various campaigns and optimize them on the go.
Ultimately, the data we have about specific consumers and the creatives we create determine the types and number of creatives that we design.
A single creative can now come in multiple formats depending on the media and customer data. Let me show you how!
First, there’s behavior data.
Based on past campaigns or market research we conduct on specific demographic, ComboApp targets a customer group based on their online activity and how they interact with ads.
For example, with the usage of browser-based cookies, we collect anonymized information about page clicks, downloads, and page-level engaged. Then, with the help of tools like google Optimizely and Google Adwords, we can extend retargeting campaigns for users who visit other websites that support Google Adwords.
Additionally, some advertising platforms also tell us demographic data points about users, such as their age, location, interests, and more.
So what do we do with all this data?
There are two ways that marketers can become more targeted and relevant with their ads: testing to optimize and testing to inform.
Testing to Optimize
Testing to optimize involves designing a test where the results can be used in a creative to drive performance.
For example, A/B testing is a form of optimization. Marketers wait for the data to come back from the experiment and analyze the results. Based on the data collected, we figure out which variation of an ad performs best, and then we use that moving forward.
An elementary A/B test can have a tremendously positive impact on the creative’s performance. Font size, copy, images, and more can all be A/B tested in a campaign – and then optimized accordingly.
Testing to Inform
Testing to inform is a method to add more value to the advertising budget.
It provides insight into the creative assets, as well as insights on the campaign as a whole.
For example, marketers may want to test how specific creative categories of products are selling, such as creative assets containing the newest products or creatives containing sale products.
While there may be a lot of work to implement correctly, there is great value for the marketing team. For example, if creative assets are performing better for the new products rather than the products on sale, the insight can be used and applied to other channels.
In a nutshell, data makes marketing more nuanced and complex, but with better results.
How Beneficial Is Data-Driven Marketing?
Personalized Content and Campaigns
First and foremost, let’s go back to the common theme around data-driven marketing in this article: it’s all about personalization.
Data-driven marketing allows businesses to reach the right people at the right time with the right message.
Marketers must be able to deliver content, products, and relevant recommendations to customers that need it, rather than sending blanket information to the masses and expecting auto-magical conversions.
Personalized messaging is critical to creating valuable relationships with your customers. And the insights created from data-driven marketing methods can produce a holistic picture of every customer – both current and prospective.
The more actionable data available to marketers, the better insights they will get into their customer’s likes, dislikes, online behavior, engagement, and more.
When marketers know their consumers at the individual level, they can predict how customers are going to react to a particular message as part of the campaign. As Brian Solis from the CMO Network expertly wrote: ‘extreme personalization is the new personalization.’
When you have actionable insights at your fingertips, as a marketer, you can make strategic decisions based on providing users with the best possible experience. Personalization should be smooth, hassle-free and offer one-to-one engagement.
With data-driven marketing, decisions can also be made faster, enabling marketers to discard what is not working and optimize what is.
Data-Driven Marketing Informs Product Development
Businesses can develop relevant products that take into account what customers really want. It will reduce the chances that the product fails when it goes to market.
With actionable user data, you can easily define features and functionalities that would be loved by your customers. Be it a website or mobile app, data-driven marketing insights reframe the conversation around what users need from your brand – and how to best provide your customers what they want.
Again, it comes back to ensuring total customer satisfaction.
With data-driven marketing, customers can access information from a variety of sources while at home or on-the-go with their smartphones.
It’s crucial for marketers to understand where users hang out online so they can start connecting with them in real-time.
Advancements in machine learning capabilities can now scan through incredibly large data sets at a fraction of the time it would take for a human to do the same work.
This gives marketers the information they need to see where consumers are most likely to convert into a sale.
Data-Driven Marketing Provides Consistency and Longevity
Data-driven marketing ensures that, in the event that there is a significant change, such as a valuable team member leaving the company, processes remain consistent.
When everyone understands the purpose of the data being collected, they can take the appropriate action. In turn, this helps with knowledge transfer and onboarding new marketers on a team.
Data-Driven Marketing Has Its Challenges
So far, we’ve covered the benefits of taking a data-driven marketing approach to marketing. To be entirely fair and transparent, though, we should also examine some of the challenges and pitfalls tied to data-driven marketing.
Finding the Right Data
Businesses generate a lot of data every day.
However, this doesn’t mean that all of it is useful. As many have argued before, a lot of marketing data collected is a total mess and difficult to turn into actionable insights.
Filtering the right data to make informed decisions is key to successful data-driven marketing. High-quality data is accurate and ‘clean’ (aka correlations and deductions can be made with a reasonable amount of confidence). When data is ‘clean’ it allows decisions to be based on factual information rather than educated guesses or interpretations.
To make the most out of data-driven marketing, marketers need to create a process that prevents inconsistencies creeping in and keep data up-to-date.
Knowing What to Ask
Wrong questions lead to irrelevant answers, resulting in incorrect information used to make business decisions.
Businesses need to pay attention to the overall marketing goals behind a product and ask the right questions that will get them the data they really need.
Asking the right questions leads to the right insights.
No two people are the same, and neither is their data.
The challenge here is unifying it to generate actionable insights.
This will require a lot of managing and analysis due to the constant advancements in the marketing industry.
Defining the right normalization data strategy is critical to creating relevant data sets.
While the collected data is great, knowing what it all means is just as important as finding the right data.
Analytics tools and services can help with this challenge, enabling businesses to make quick and informed decisions. They can also help to understand which marketing activities are having the most significant impacts on customers.
While technology can help, data is usually stored in a single location.
Integrated analytics tools are essential for linking data to create a cohesive picture. Big data gets increasingly bigger every day.
Ultimately, being able to bring everything together will determine how successful the campaign will be.
This is one of the most severe problems that data-driven marketing runs into.
Unsuitable technology can contribute to all of the challenges listed above, such as providing the wrong data and not transforming it into a digestible and actionable plan.
Marketers must find the right tools that will give them the results they need to meet department and business goals.
The Building Blocks Of Data-Driven Marketing – The Technology Stack
The marketing technology stack focuses on measuring the impact of activities for more efficient processes.
With many marketing technologies available across an ever-growing number of industries, marketers need to stay ahead of the curve and take advantage of these solutions while they can.
At the same time, marketing teams must know which technologies are best suited to their business or clients.
A standard data-driven marketing stack is made up of 3 foundational building-blocks:
1) Campaign management
2) Analytics and reporting
3) Attribution and optimization
This technology refers to the creation of campaign groups targeting specific user types and tracking how effective different campaigns are at a given moment in time.
Send personalized content, reminders, updates, special offers, etc. to the people that require each variation.
One of the most common forms of marketing is through email campaigns, and there are lots of technologies that can help.
For example, MailChimp can be used to manage email marketing campaigns.
It allows marketers to sync data and content from third-party services and learn how each campaign is affecting the business. It will also provide tips for improving ongoing campaigns, as well as insights into their effectiveness.
Another useful campaign management tool is Aweber. A great feature of this technology is its autoresponder. Its analytics capabilities are one of the best around, and overall, the tool is straightforward to use.
Analytics and Reporting
Analytics tools provide granular information about the groups targeted by various marketing campaigns, such as how users behave and how they interact with a specific campaign (likes, shares, sales, social shout-outs, etc.).
This information is useful to marketers because they can optimize the customer experience and develop relationships that last to create loyalty to the brand.
Robust analytics reporting creates a logical output of the data to enable marketers to make informed decisions. But it also helps with data visualization techniques that can be distributed among internal stakeholders via such as graphs, tables, and pie charts. Standalone reporting solutions aggregate activity and performance into one place. For reference, reporting software is also referred to as marketing dashboards.
Again, there are a lot of analytics tools on the market.
Perhaps the most common analytics tool out there is Google Analytics. GA is free to use and can help businesses develop a better strategy through campaign tracking and customized data reports. GA also allows for goal settings and monitoring various funnels on a website/ mobile app.
Additionally, Google Analytics can be synced up to a lot of reporting software like Google Data Studio, as well as the campaign management tools like the aforementioned Aweber.
For businesses that are keen to utilize social media for their campaigns, it may be useful to leverage specialized marketing analytics tools like Sprout Social. This technology allows teams to see the keywords their brand is being linked with across various social channels, including data collected from the number of competitors on each platform.
Once marketers have access to the right data, they can refine various marketing campaigns and make improvements over time. When a business understands the contributions to marketing activities, they can begin to deploy their budget more effectively.
For example, Jive is a collaboration software that connects users and team members. It is used to optimize engagement online and identify influencers.
Analytics services like Amplitude can be used by marketers to measure conversion rates and customer behavior.
One of Amplitude’s unique features is that it maps out the exact route that customers take to achieve specific conversion goals.
Another key feature Amplitude is famous for refers to a web analytics concept they pioneered: a cohort analysis.
Amplitude was the first analytics provider who understood that different users behave differently on a website. And they provided the functionality to marketers and product leaders to define specific audiences that can be segmented and analyzed on their own. Through cohort analysis, marketers can make better decisions about their digital products and optimizing various digital campaigns over time.
Invest in SEO as Part of Your Data-Driven Marketing Campaign
SEO is a crucial strategy for increasing organic traffic through search engines to the website. SEO works well with content marketing, and there are many tools that can help with keyword research, such as Ahrefs, which we often use in our SEO campaigns for our clients.
As we wrote in the past, SEO and content strategy are some of the most effective strategies to attract new customers, see how customers interact with your website or mobile app and test out various conversion campaigns on your platform.
Invest in a Robust Content Management System
A robust CMS allows for the easy creation and management of content, which is why we consider it a pivotal data-driven marketing foundational building block.
Examples of Data-Driven Marketing
Now that we know what data-driven marketing is, let’s review some tangible examples of how it is used today.
Data-Driven Email Marketing
We have already seen that email marketing is one of the most popular strategies. However, data-driven email marketing can take it to another level and tailor it to each and every customer, rather than just groups of customers.
Marketing teams can create content based on an individual’s preferences, making it the perfect way to build relationships.
On some of the most complex projects we’ve worked on, we’ve created up to 50 different variations of emails based on specific marketing personas identified for our clients. The more relevant an email becomes, the higher the chances it has to convert a user.
Marketers can use retargeting to advertise to potential customers even if they leave your website or mobile app. Many online visitors tend to browse the internet for more than one reason, so why not appeal to them after they leave your website?
This data-driven advertising method gives consumers a gentle reminder about the product or service they had previously looked at. It can be particularly effective across social media since 30% of all time spent online is on these platforms.
Also, consider these amazing stats from Invesp about retargeting:
- 4 in 5 consumers notice retargeting ads.
- 1 in 5 marketers now has a budget dedicated to retargeting campaigns.
- 46% of SEM professionals say retargeting is the most underused marketing technique.
- The average clickthrough rate for regular ads is 0.07% versus retargeting ads, which is 0.7% (a 900% increase in CTR!).
- Retargeted customers are 3x more likely to click on your ad than those who see your advertisement for the first time.
Retargeting can also be combined with technologies to create hyper-specific marketing campaigns for certain customers.
For example, if a current customer purchased a cellphone, retargeting could be used to offer that customer, accessories like a case, screen protector, or charger.
Retargeting is one of the most popular – and effective – data-driven marketing techniques ever invented! And we have Google to thank for that!
Data-driven advertising can be used by marketers to reach their target audience, regardless of their location.
Data insights and automation technology can create personalized adverts that increase click-through rates and conversion rates.
Each individual has different needs. The data collected about these needs allows marketers to be precise with their efforts by selecting content that will have the most significant impact. Actionable insights allow for targeting against specific buyer personas which, when combined with machine learning and other marketing technologies, can produce more effective advertising to drive better clicks and conversions.
Again, social media is a great channel to implement data-driven advertising, with Facebook proving to be effective for advertising in particular.
Facebook users are clicking on ads more and more every year, with data-driven ads being the primary driver behind this increase in engagement with Facebook ads.
Acting Based on Marketing Trends
Businesses can feel cautious testing new channels when an existing method is working well. After all, why take the risk?
Using marketing trends from various channels leads to building a more efficient and optimized marketing process. This is done by running PPC campaigns for a short amount of time until the keyword search volume is known.
PPC campaigns can also be used to determine if specific keywords have commercial intent. This gives marketers a better estimation if the keywords are worth going after. At ComboApp, we use the Ahrefs content explorer functionality, but you can also use SEO marketing trends to decide on how to market specific demographics.
All Is Not Great With Data-Driven Marketing
While data is great, decisions should not be just made based on what customers do, they should also factor why customers do it. That is the qualitative aspect of things.
There are some suggestions that data-driven marketing is not driven by data at all. This is because it’s based on the assumption that because something worked in the past, it is going to work now and in the future.
After all, the marketing and advertising industry knows all too well that trends and customer preferences can change in the blink of an eye.
Furthermore, data-driven marketing is, in some ways, killing the creativity that fueled earlier generations of marketers. Fostering creativity can enable companies to make 10% more revenue than their peers.
But focusing on creatives doesn’t mean that businesses should ignore data altogether. The best marketing teams strike a balance between the science of data-driven marketing and the art of creativity to see optimal results.
Over 50% of marketing campaigns are attributed to the creative element. Businesses can have data of the highest quality, but it will fail if it doesn’t resonate with the end consumer.
Data-driven marketing is here to stay.
Success will come from fine-tuning the data and getting creative on how to reach out to customers. The challenges need to be addressed first and a robust strategy created following that.
This article covered:
- Where data-driven marketing came from and how it has evolved;
- How marketers can take advantage of data-driven marketing;
- The challenges marketing teams face;
- Real-world examples of it being used.